On the Vulnerability of Ghost Domain Names

2014 ◽  
Author(s):  
Hiroaki Kikuchi ◽  
Tomohiro Arimizu
Keyword(s):  
Domain Names

scholarly journals Real-Time Detection of Dictionary DGA Network Traffic Using Deep Learning

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
Kate Highnam ◽  
Domenic Puzio ◽  
Song Luo ◽  
Nicholas R. Jennings
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Real Time ◽  
Network Traffic ◽  
Short Term Memory ◽  
Domain Names ◽  
Control Networks ◽  
Detection Techniques ◽  
Lstm Network ◽  
And Control

AbstractBotnets and malware continue to avoid detection by static rule engines when using domain generation algorithms (DGAs) for callouts to unique, dynamically generated web addresses. Common DGA detection techniques fail to reliably detect DGA variants that combine random dictionary words to create domain names that closely mirror legitimate domains. To combat this, we created a novel hybrid neural network, Bilbo the “bagging” model, that analyses domains and scores the likelihood they are generated by such algorithms and therefore are potentially malicious. Bilbo is the first parallel usage of a convolutional neural network (CNN) and a long short-term memory (LSTM) network for DGA detection. Our unique architecture is found to be the most consistent in performance in terms of AUC, $$F_1$$ F 1 score, and accuracy when generalising across different dictionary DGA classification tasks compared to current state-of-the-art deep learning architectures. We validate using reverse-engineered dictionary DGA domains and detail our real-time implementation strategy for scoring real-world network logs within a large enterprise. In 4 h of actual network traffic, the model discovered at least five potential command-and-control networks that commercial vendor tools did not flag.

scholarly journals DomainChroma: Building actionable threat intelligence from malicious domain names

2018 ◽  
Vol 77 ◽  
pp. 138-161 ◽  
Author(s):  
Daiki Chiba ◽  
Mitsuaki Akiyama ◽  
Takeshi Yagi ◽  
Kunio Hato ◽  
Tatsuya Mori ◽  
...  
Keyword(s):  
Domain Names ◽  
Threat Intelligence

icann’s New Generic Top-Level Domain Names Dispute Resolution Procedure Viewed Against the Protection of the Public Interest of the Internet Community: Litigation Regarding Health-Related Strings

2014 ◽  
Vol 13 (3) ◽  
pp. 306-346 ◽  
Author(s):  
Simone Vezzani
Keyword(s):  
Freedom Of Expression ◽  
The Internet ◽  
Commercial Arbitration ◽  
Domain Names ◽  
Internet Users ◽  
Health Related ◽  
Rules Of Procedure ◽  
Rights Discourse ◽  
The Right ◽  
Human Rights Discourse

icann’s decision to liberalize the market for Internet Generic Top-Level Domain Names has been giving rise to many concerns, related in particular to the registration of health-related strings, which may favour fraud and the dissemination of misleading health information. However, a very sophisticated mechanism has been put into place by icann, intended to prevent the registration of strings which face opposition from a significant portion of the community they purportedly aim to serve, or which are contrary to generally accepted principles related to morality and public order. Tailored after the model of commercial arbitration, icann rules of procedure are noteworthy in that they give standing to all interested Internet users and to an Independent Objector. Though underlining some of its procedural deficiencies, this article emphasizes the importance of the icann mechanism in the “constitutionalization” of the Internet. It also discusses the contribution of icann expert panels to international human rights discourse, as illustrated by the expert panel determinations walking the tightrope between freedom of expression and the right to health.

Urdu Domain Names

2006 ◽  
Author(s):  
Sarmad Hussain ◽  
Nadir Durrani
Keyword(s):  
Domain Names

Analysis and Detection on Abused Wildcard Domain Names Based on DNS Logs

2019 ◽  
pp. 211-225
Author(s):  
Guangxi Yu ◽  
Yan Zhang ◽  
Huajun Cui ◽  
Xinghua Yang ◽  
Yang Li ◽  
...  
Keyword(s):  
Domain Names
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